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Summarization
Summarization#
Summarization involves creating a smaller summary of multiple longer documents.
This can be useful for distilling long documents into the core pieces of information.
The recommended way to get started using a summarization chain is:
from langchain.chains.summarize import load_summarize_chain
chain = load_summarize_chain(llm, chain_type="map_reduce")
chain.run(docs)
The following resources exist:
Summarization Notebook: A notebook walking through how to accomplish this task.
Additional related resources include:
Utilities for working with Documents: Guides on how to use several of the utilities which will prove helpful for this task, including Text Splitters (for splitting up long documents).
CombineDocuments Chains: A conceptual overview of specific types of chains by which you can accomplish this task.
Data Augmented Generation: An overview of data augmented generation, which is the general concept of combining external data with LLMs (of which this is a subset).
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By Harrison Chase
    
      © Copyright 2023, Harrison Chase.
      
  Last updated on Mar 22, 2023.